March 3, 2026Open Access

Detection of Taiqiu sweet persimmons during the color-transition period with an improved YOLO11-FC2T model and causal analysis

Key Points

Detection of persimmons during the color-transition period shows improved accuracy, enhancing automated identification.
YOLO11-FC2T demonstrates reliable generalization ability with significant stability improvements for fruit counting.
Using an enhanced YOLO11-FC2T model, detection challenges specific to color transitions in fruit are effectively addressed, leading to better agricultural practices.
This improvement supports more precise agricultural operations, with potential benefits for crop monitoring and management.

Abstract

Overall, YOLO11-FC2T addresses key detection challenges during the color-transition period and provides a practical, portable solution for automated fruit identification and counting in precision agriculture. The above results indicate that YOLO11-FC2T not only improves the indicators, but also possesses reliable generalization ability and stability.

Detection of Taiqiu sweet persimmons during the color-transition period with an improved YOLO11-FC2T model and causal analysis

Key Points

Abstract

Cite This Study